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Farmers in the developing world frequently find themselves in uncertain and risky environments: often having to make decisions based on very little information. Functional models are needed to support farmers tactical decisions. In order to develop an appropriate model, a comparison is carried out of potential modelling approaches to address the question of what to grow where. A probabilistic GlS model is identified in this research as a suitable model for this purpose. This model is implemented as the stand-alone Spatial Decision Support System (SDSS) CaNaSTA, based on trial data and expert knowledge available for Central America and forage crops. The processes and methods used address many of the problems encountered with other agricultural DSS and SDSS. CaNaSTA shows significant overlap with recommendations from other sources. In addition, CaNaSTA provides details on the likely adaptation distribution of each species at each location, as well as measures of sensitivity and certainty. The combination of data and expert knowledge in a spatial environment allows spatial and aspatial uncertainty to be explicitly modelled. This is an original approach to the problem of helping farmers decide what to plant where.

Agroforestry production methods present one option for addressing growing concerns about the long term sustainability of intensive coffee production techniques. A study was designed to compare the effects of fertilization and shading from two leguminous species, Erythrina poeppigiana and Chloroleucon eurycyclum, on coffee grown at a Costa Rican research site. Coffee below biannually pruned, conventionally fertilized Erythrina exhibited the highest photosynthetic performance under both low and high light levels as well as greater biomass and higher N concentration. Soil P did not affect coffee performance, although shade trees on sites with higher soil P fixed more N compared to trees grown on low P sites, most of which were not found to be fixing. Results suggest shade mechanisms are the most important drivers of coffee adaptation in coffee agroforestry systems, though proper soil nutrient management and legume species pairing also appear to augment coffee response to microclimate conditions.

Agroforestry production methods present one option for addressing growing concerns about the long term sustainability of intensive coffee production techniques. A study was designed to compare the effects of fertilization and shading from two leguminous species, Erythrina poeppigiana and Chloroleucon eurycyclum, on coffee grown at a Costa Rican research site. Coffee below biannually pruned, conventionally fertilized Erythrina exhibited the highest photosynthetic performance under both low and high light levels as well as greater biomass and higher N concentration. Soil P did not affect coffee performance, although shade trees on sites with higher soil P fixed more N compared to trees grown on low P sites, most of which were not found to be fixing. Results suggest shade mechanisms are the most important drivers of coffee adaptation in coffee agroforestry systems, though proper soil nutrient management and legume species pairing also appear to augment coffee response to microclimate conditions.

The distribution of wild biodiversity in agroecosystems affect crop performance and yield in various ways. In this thesis I have studied the impact of wild biodiversity, in terms of trees and forest structures, on crop pests, pollinators and the pollination services provided in a heterogeneous landscape in southwestern Ethiopia.  Coffee, Coffea arabica, is a forest shrub native to Ethiopia and is grown in most wooded areas in the landscape where I conducted my studies. Wild coffee is still found in remote parts of the forests in the landscape. For my first paper, I surveyed pest damage on coffee in coffee forest sites, where some sites were situated in continuous forest and some in isolated forest patches. I found the variation in pest damage frequency to mainly be among coffee plants within a site, rather than among sites, which indicates the importance of local processes. However, some pests were clearly connected to the forest habitat, such as the olive baboon. In my second study, I surveyed pollinators visiting coffee flowers across a gradient of shade-tree structures. I found the semi-wild honeybee to be the dominating flower visitor. The abundance of the honeybee was not related to shade-tree structures, but to amount of coffee flower resources in the site. On the other hand, other pollinators, which included other bee species and hoverflies, were positively affected by more shade trees in the site. In my third study I investigated how the forest cover affected local bee communities in the agricultural landscape. Moreover, I investigated if this relationship differed between the dry and rainy season. The distribution of food resources for bees changes between the seasons, which may affect the bees. Most trees, fruit trees and coffee, which are patchy resources, flowers in the dry season, whereas most herbs and annual crops, which are more evenly spread resources, flowers during the rainy season. I found a clear turnover in bee species composition between the dry and rainy season, with more mobile species in the dry season. Increased forest cover in the surrounding landscape had a positive impact on bee abundance and species richness. However, the impact did not change between seasons. In my fourth study I evaluated the pollination success and pollen limitation of a common oil crop in the landscape in relation to forest cover. I found severe pollen limitation across the landscape, which may be related to the observed low bee abundances. The pollen limitation was not related to surrounding forest cover. In conclusion, I have found the forest and wooded habitats to impact several mobile animals and pathogens in our study landscape, which in turn affect people. However, there is large complexity in nature and general relationships between forest structures and all crop related organisms may be unlikely to find. Various species are dependent on different resources, at different spatial scales and are interacting with several other species. To develop management strategies for increased pollination services, for reduced pest damage or for conservation in the landscape, more species-specific knowledge is needed. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: Manuscript.</p>

Over the past decades, public concern about global environmental change has grown, following the progressive increase in both frequency and intensity of extreme events. Even though the problem is global, it has proved to have very different societal and environmental impacts at local level, further widening the gap between disadvantaged and advantaged communities, according to the degree of vulnerability of their social, economic and environmental systems. Among the various anthropogenic activities, the agricultural sector is particularly linked to global environmental change by a two-way relationship: on the one hand, intensive mono-cultures, together with intensive livestock production, compromise the environment and produce huge CO$_2$ emissions (one of the most important factors behind global warming); on the other hand, smallholder farming is one of the most endangered sectors by global environmental change, precisely because it depends heavily on the natural resources of the territory, including favourable weather and climate. Scientific research, supported by international institutions, has been working on this subject for several decades, analysing phenomena at global and local scale and providing medium and long-term forecasts capable of directing economic and political strategies. Such complex investigations become even more complex in contexts lacking reliable environmental data, where their low-quality and low representativeness weaken their reliability, compromising the reliability of the outcomes as well. This thesis seeks to respond to the increasing need of realistically addressing environmental phenomena that threaten rural communities and the environment on which they depend in low-income countries, by investigating two of the main environmental factors affecting tropical farming practices: river-floodplain dynamics and climate change. Despite data-related constraints, the environment of tropical rural areas still provides a unique opportunity to study several near-natural processes, such as the morphodynamics of mostly free-flowing rivers. Especially in foothill regions, unconfined or partially confined conditions of tropical rivers allow evaluating the natural dynamics of erodible river corridors, with erosion and accretion shaping their interactions with the adjacent floodplain and related human activities. At the same time, the complex terrain characterizing the river valleys at the foothills of high mountain chains also offers the opportunity to study interesting local meteorological processes, especially considering the interaction between synoptic-scale dynamics and local convective phenomena. In this context, local bottom-up initiatives and new and tailored-to-context strategies for adaptation to the ongoing environmental change are deepened following a multidisciplinary approach. This PhD research has been framed within an international cooperation project entitled “Sustainable Development and Fight against Climate Change in the Upper Huallaga basin (Peru)”, promoted by Mandacarù ONLUS, and funded by the Autonomous Province of Trento. The project aimed to enhance the resilience of the local farmers of the Upper Huallaga valley (Peru), facing the consequences of climate change and implementing new agricultural initiatives with a special attention to plantain and banana fields. Thanks to the support of the involved partners (Redesign by PROMER s.a.c., the Universidad Agraria Nacional de la Selva de Tingo Maria, in Peru, and the Edmund Mach Foundation of San Michele all’Adige, in Italy), the project provided the opportunity to carry out a consistent set of fieldwork activities over an 8-months period collecting hydro-morphological data, interviewing the local population, and installing two weather stations. The PhD thesis has been structured along two main parts, related to to the assessment of climate change effects on local agricultural practices, and the interplay between river-floodplain dynamics and floodplain agriculture. The part on the assessment of climate change includes two main research elements. First, a novel approach is used to evaluate climate change in data-scarce contexts: non-conventional data sources (population survey) are compared with conventional data sources (few local historical weather stations and global reanalysis data series – ERA5), to better account for the sub-daily time scale (local conventional sources only provide daily data), correlating weather changes perceived by farmers (more thunderstorms and longer drought periods) with climate variations deduced from quantitative data. Second, after having determined the most impacting meteorological variables on crops through the survey, a weather early-warning system has been developed to provide agro-meteorological forecasts to the \textit{bananeros} (banana farmers) of the Upper Huallaga valley. The system, based on the Weather Research and Forecasting (WRF) model, and enhanced with the assimilation of real-time observations from local meteorological stations installed during the project fieldwork, issues an alert when the predicted wind speed exceeds thresholds related to potential damage to the harvest, and spreads the warning via text messages. Such alerting system contains several novel features in relation to the socio-environmental context, allowing to discuss its potential for replication in analogous, vulnerable situations. The part on river-floodplain dynamics also includes two main research elements. First, a remote-sensing analysis is conducted at reach scale in two different reaches of the Huallaga River, quantifying geomorphological river trajectories and land use changes in the adjacent floodplain. The outcomes show that river morphology reacts differently depending on the agricultural systems (extensive or intensive) in the nearby floodplain, revealing a high geomorphological sensitivity of such a near-natural, highly dynamic river reach. Second, riverine agriculture within the erodible river corridor is analysed in association with riverine islands dynamics, at the geomorphic unit scale, evaluating the morphological evolution and agricultural suitability of two cultivated fluvial islands. The three main drivers of agricultural suitability within river erodible corridors, i.e. river disturbance, cultivation windows of opportunity, and soil suitability are quantified, allowing to generalize a process-based conceptual model of riverine islands as complex-adaptive-systems.